Software Engineering Management Research Articles

REQUIREMENTS GATHERINGS AND IMPLEMENT ISSUES

Summary of the Research Research goal is better understanding and learning by using old and new techniques for resolve problems and empty blank spaces which are mostly facing during requirement gathering phase to development phase. This paper mainly purpose gathering research on Software requirements gathering and their effect on all incoming challenges and cost, benefits. Requirements is one in technology application style and development. . Most of the projects are fail due to gathering the poor requirement gathering. Many of the software based projects acquired by one to one the interview for requirement gathering. During last few years new software development approaches were introduced for increase software product which are helpful for reduce cost, time, and effort. For all procedure Software Requirement gathering is the one of the special key. Requirement gathering is the most important area in Software Engineering and project management.

A Preliminary Study on the Innovation and Perfection Strategy of Computer Software Engineering Management

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Machine Learning: A Software Process Reengineering in Software Development Organization

BPR (Business Process Re-engineering) is an organizational mechanism that improves the organizational ability in responding to the challenges of qualitative result by change management and improvement in software engineering processes, productivity, product quality and competitive advantage. BPR inherits, explores and implements the building of process change, to incorporate enhancements to the essential considerations and protocols of (SEM) Software Engineering Management. Machine Learning (ML) can be the key aspect for BPR in software development organization. The goal of this research study is raising the conceptual vision about integration of automation technology like ML and its life cycle development within Software Development Life Cycle (SDLC) of the software product and highlights benefits and drawbacks ML techniques in SPM (Software Project Management), and how to implement ML in standard SEM practices. We have attempted the introduction of machine learning in SEM to determine specific performance and tasks reuse using empirical analysis and discussion on implementation of ML algorithms. The empirical study of software technologies includes control structure of an autonomous software application. In current era, ML imparts consistently promising accuracy in some SEM fields. The goal of this paper is an empirical and analytical study and literature review to propose desired level of quality software, through the comparative evaluation of existing processes and their respective support for Software Quality Engineering (SQE).

Business Process Reengineering: A Scope of Automation in Software Project Management using Artificial Intelligence

This research paper aims an analytical study on the software development organization insight into trending automation technologies and their implementation Software Engineering Management (SEM) processes. Software Project Management (SPM) is a scientific art for planning, controlling execution and monitoring. SPM approaches are more focusing towards the essential requirement for the success of software project development. It has been very challenging to manage software development using existing project management procedures driven by software development organizations and this is one of the areas of problem statement for this research. This paper discusses an analytical study for the requirements and consideration of BPR in SPM, explores to spot and emphasizes the important success factors for the execution of a BPR using benefits of Artificial Intelligence (AI) in software development organization. BPR is organizational mechanism that improves ability to respond to challenges of qualitative result by change and improvement in software engineering processes, productivity, product quality and competitive advantages. AI will be the best approach and scope of automation SEM processes for software development organizations. This paper also represents a conceptual view of software engineering model shift for improvements in capability of project managers to handle agile thinking and problem solving for betterment of SPM using Artificial Intelligence.

Determining Information Security Threats for an IoT-Based Energy Internet by Adopting Software Engineering and Risk Management Approaches

This paper introduces an information security threat modeling (ISTM) scheme, which leverages the strengths of software engineering and risk management approaches, called I-SERM. The proposed I-SERM scheme effectively and efficiently prioritizes information security threats for IT systems that utilize a large number of sensors, such as Internet of Things (IoT)-based energy systems. I-SERM operations include determining functional components, identifying associated threat types, analyzing threat items, and prioritizing key threats with the use of software engineering tools such as product flow diagrams, use case diagrams, and data flow diagrams. By simultaneously referring to a proposed STRIDE+p matrix and a defined threat breakdown structure with reference score (TBS+r) scheme, the I-SERM approach enables systematic ISTM. To demonstrate the usability of I-SERM, this study presents a practical case aimed at electricity load balancing on a smart grid. In brief, this study indicates a substantive research direction that combines the advantages of software engineering and risk management into a systematic ISTM process. In addition, the demonstration of I-SERM in practice provides a valuable and practical reference for I-SERM application, and contributes to research in the field of information security designs for IoT-based Energy Internet systems.

Trends in Occurrences of Systems Engineering Topics in Literature

Examining past research using content analysis can provide detailed information about the trends a discipline has displayed over years or decades. Disciplines such as software engineering and hospitality management have used methods for analyzing topic frequencies in the past. This paper uses similar methods to study the presence of systems engineering topics in literature to understand the occurrence of approaches and metrics in the community over time. This paper reviews the trends of systems engineering topics over the years 1998–2016 by performing a content analysis of four systems engineering and design engineering journals. A mathematical analysis of the trends is performed using rank ordering and a rank correlation metric. The study shows that model-based approaches have grown significantly since the early 2000s, as advocated in the INOCSE MBSE initiative, while other approaches such as Taguchi’s method and axiomatic design have been seen less frequently in literature. Systems engineering metrics that have been frequently seen in literature include complexity, reliability, and quality. The results from this research provide a portrait of the systems engineering landscape.

A Constraint-Based Declarative Programming Framework for Scheduling and Resource Allocation Problems

Scheduling and resource allocation problems are widespread in many areas of today’s technology and management. Their different forms and structures appear in production, logistics, software engineering, computer networks, project and human resources management, services, etc. The literature (problem classification, scheduling and resource allocation models, solutions) is vast and exhaustive. In practice, however, classical scheduling problems with fixed structures and standard constraints (precedence, disjoint, etc.) are rare. Practical scheduling problems include also logical and nonlinear constraints, and they use nonstandard criteria of schedule evaluations. Indeed, in many cases, decision makers are interested in the feasibility and/or optimality of a given schedule for specified conditions formulated as general and/or specific questions. Thus, there is a need to develop a programming framework that will facilitate the modeling and solving of a variety of diverse scheduling problems. The framework should be able to (a) model any types of constraints, (b) ask questions/criteria relating to the schedule execution mode and (c) be highly effective in finding solutions (schedule development). This paper proposes such a constraint-based declarative programming framework for modeling and solving scheduling problems which satisfies the assumptions above. It was built with the Constraint Logic Programming (CLP) environment and supported with Mathematical Programming (MP). The functionality and effectiveness of this framework are presented with the use of an illustrative example for the resource-constrained scheduling problem with additional resources.

Complexity metrics for DMN decision models

Complexity impairs the maintainability and understandability of conceptual models. Complexity metrics have been used in software engineering and business process management (BPM) to capture the degree of complexity of conceptual models. The recent introduction of the Decision Model and Notation (DMN) standard provides opportunities to shift towards the Separation of Concerns paradigm when it comes to modelling processes and decisions. However, unlike for processes, no studies exist that address the representational complexity of DMN decision models. In this paper, we provide an initial set of complexity metrics for DMN models. We gather insights from the process modelling and software engineering fields to propose complexity metrics for DMN decision models. Additionally, we provide an empirical complexity assessment of DMN decision models. For the decision requirements level of the DMN standard 19 metrics were proposed, while 7 metrics were put forward for the decision logic level. For decision requirements, the model size-based metrics, the Durfee Square Metric (DSM) and the Perfect Square Metric (PSM) prove to be the most suitable. For the decision logic level of DMN the Hit Policy Usage (HPU) and the Total Number of Input Variables (TNIV) were evaluated as suitable for measuring DMN decision table complexity.

A Domain Ontology for Software Requirements Change Management in Global Software Development Environment

Ontology and its role in both software engineering and knowledge management fields have been widely reported in the literature. Numerous studies have proven the effectiveness of using ontologies to support the process of requirements engineering. One of the main problems facing requirements engineering is that the requirements are exposed to change. In fact, this problem swells even more in global software development (GSD) environment. Given that this problem is unavoidable, we need to improve the requirements change management (RCM) process. In this paper, a systematic domain ontology for RCM especially in GSD environment is proposed. A hybrid method combining Methontology and the 101 method is used for its development; Web Ontology Language (OWL) for its representation; and Protege for its implementation. It was validated using ontology content evaluation and competency question evaluation methods. Also, it was verified using both ontology taxonomy evaluation and FOCA evaluation methods. Validation and verification results showed that the proposed ontology was successfully built. Building this ontology can be considered as a base contribution in supporting the RCM process in GSD.

Regularized Fuzzy Neural Networks to Aid Effort Forecasting in the Construction and Software Development

Predicting the time to build software is a very complex task for software engineering managers. There are complex factors that can directly interfere with the productivity of the development team. Factors directly related to the complexity of the system to be developed drastically change the time necessary for the completion of the works with the software factories. This work proposes the use of a hybrid system based on artificial neural networks and fuzzy systems to assist in the construction of an expert system based on rules to support in the prediction of hours destined to the development of software according to the complexity of the elements present in the same. The set of fuzzy rules obtained by the system helps the management and control of software development by providing a base of interpretable estimates based on fuzzy rules. The model was submitted to tests on a real database, and its results were promissory in the construction of an aid mechanism in the predictability of the software construction.

INCOSE Working Group Addresses System and Software Interfaces

ABSTRACTIn the 21st century, when any sophisticated system has significant software content, it is increasingly critical to articulate and improve the interface between systems engineering and software engineering, that is the relationships between systems and software engineering technical and management processes, products, tools, and outcomes. Although systems engineers and software engineers perform similar activities and use similar processes, their primary responsibilities and concerns differ. Systems engineers focus on the global aspects of a system. Their responsibilities span the lifecycle and involve ensuring the various elements of a system—such as hardware, software, firmware, engineering environments, and operational environments—work together to deliver capability. Software engineers also have responsibilities that span the lifecycle, but their focus is on activities to ensure the software satisfies software‐relevant system requirements and constraints. Software engineers must maintain sufficient knowledge of the non‐software elements of the systems that will execute their software, as well as the systems their software must interface with. Similarly, systems engineers must maintain sufficient awareness of the software to enable early identification and resolution of software risks and issues driven by other system elements. Thus, to enable continued progress in creating and sustaining capability in complex, interconnected systems, systems and software engineers must commit to improving the interfaces between their disciplines, to aligning and integrating their terminology, processes, methods, and tools.Recognizing the need to improve the system engineering‐software engineering interface, INCOSE approved the charter of the System and Software Interface Working Group (SaSIWG) in 2017. At its initial meeting at the INCOSE International Symposium 2017 (IS 2017) in Adelaide, Australia, the SaSIWG derived working group objectives from lists of brainstormed systems and software issues. This paper documents the interface issues elicited, grouped into seven categories, along with system‐ software interface use cases identified by SaSIWG members. The interface issues and use cases expose questions for the SaSIWG to prioritize and respond to. The paper concludes with a summary of the SaSIWG's plan to respond to these questions and strengthen the interface between the systems engineering and software engineering disciplines.

What Makes a Great Manager of Software Engineers?

Having great managers is as critical to success as having a good team or organization. In general, a great manager is seen as fuelling the team they manage, enabling it to use its full potential. Though software engineering research studies factors that may affect the performance and productivity of software engineers and teams (like tools and skills), it has overlooked the software engineering manager. The software industry's growth and change in the last decades is creating a need for a domain-specific view of management. On the one hand, experts are questioning how the abundant work in management applies to software engineering. On the other hand, practitioners are looking to researchers for evidence-based guidance on how to manage software teams. We conducted a mixed methods empirical study of software engineering management at Microsoft to investigate what manager attributes developers and engineering managers perceive important and why. We present a conceptual framework of manager attributes, and find that technical skills are not the sign of greatness for an engineering manager. Through statistical analysis we identify how engineers and managers relate in their views, and how software engineering differs from other knowledge work groups in its perceptions about what makes great managers. We present strategies for putting the attributes to use, discuss implications for research and practice, and offer avenues for further work.

Software startup engineering: A systematic mapping study

Software startups have long been a significant driver in economic growth and innovation. The on-going failure of the major number of startups calls for a better understanding of state-of-the-practice of startup activities. Objective With a focus on engineering perspective, this study aims at identifying the change in focus of research area and thematic concepts operating startup research.A systematic mapping study on 74 primary papers (in which 27 papers are newly selected) from 1994 to 2017 was conducted with a comparison with findings from previous mapping studies. A classification schema was developed, and the primary studies were ranked according to their rigour.We discovered that most research has been conducted within the SWEBOK knowledge areas software engineering process, management, construction, design, and requirements, with the shift of focus towards process and management areas. We also provide an alternative classification for future startup research. We find that the rigour of the primary papers was assessed to be higher between 2013–2017 than that of 1994–2013. We also find an inconsistency of characterizing startups.Future work can focus on certain research themes, such as startup evolution models and human aspects, and consolidate the thematic concepts describing software startups.

Leveraging Big Data From Open Source to Improve Software Project Management

Software engineering management research has been conducted for many years. Researchers have faced a myriad of challenges in obtaining reliable data and associated metrics, developing practical estimating models, and influencing project improvements within industry. Open source software (OSS) can be leveraged to address these issues. This paper explores how big data from OSS can improve software engineering and management practices. The authors begin to explore a select few metrics to predicting process quality. Improved software engineering management methods are identified. It is expected that these tangible research outcomes would be of keen interest to practitioners.

Managing Programmers, with Ron Lichty

Veteran software manager Ron Lichty joins Nate Black to share his insights on managing software engineers. Nate and Ron delve into what about this is hard, how to grow as a manager, and what makes highly performing teams.

Information systems ethics – challenges and opportunities

PurposeThe purpose of this paper is to explore the ethical issues surrounding information systems (IS) practice with a view to encouraging greater involvement in this aspect of IS research. Information integrity relies upon the development and operation of computer-based information systems. Those who undertake the planning, development and operation of these information systems have obligations to assure information integrity and overall to contribute to the public good. This ethical dimension of information systems has attracted mixed attention in the IS academic discipline.Design/methodology/approachThe authors are a multidisciplinary team providing a rich, diverse experience which includes professional and information ethics, management information systems, software engineering, data repositories and information systems development. Each author has used this experience to review the IS ethics landscape, which provides four complimentary perspectives. These are synthesised to tease out trends and future pointers.FindingsIt is confirmed that there is a serious lack of research being undertaken relating to the ethical dimension of the Information Systems field. There is limited crossover between the well-established multidisciplinary community of Computer Ethics research and the traditional Information Systems research community.Originality/valueAn outline framework is offered which could provide an opportunity for rich and valuable dialogue across the two communities. This is proposed as the starting point for a proactive research and practice action plan for information systems ethics.

Sustaining Software for Biological Collections Computing

Specify is a biological collections data management platform for the digitization, curation, and dissemination of museum specimen information. The Specify Software Project and its predecessor, the MUSE Project, have been funded by the US National Science Foundation for 30 years. Specify 6, a native desktop app is used in about 500 biological collections for specimen data processing. The latest generation, Specify 7, is a web platform for hosting collections data in the Specify Cloud service or on an institutional server. During 2017 and 2018, with encouragement from its long-time funder, the Specify Project is 'transitioning-to-sustainability', in a campaign to identify an organizational structure and sources of revenue to support the Project's software engineering, help desk and data management services. A museum consortium dedicated to maintaining and evolving Specify Software is a probable outcome. Such a non-profit consortium would formally engage institution directors, collections researchers, and biodiversity informaticists in the governance of Specify. Each group would play a significant role in determining the direction and capabilities of consortium software products and services. In this paper, we will summarize our approach with the Specify transition. The Specify Project's transition to sustainability is not unique within the research museum community. In the United States, groups that produce Symbiota, Arctos, and GeoLocate, as examples, face a similar quest. As legacy funders look to data communities to underwrite more of the ongoing expense of research cyberinfrastructure, projects seeded with grant funds that contribute to the overall suite of collections digitization and management software solutions will, sooner or later, face this existential challenge. Significant questions of research community economics present themselves. How much can collections institutions, of all sizes and budgets, afford to pay for specimen data software platforms and services? Will the significant cost of collections software development and support lead to sustained, collaborative, community-wide efforts, similar to the way that members of professional societies pool resources (including endowments) to provide journal and annual meeting 'infrastructure'? Or will the high cost of software, security and systems management, etc., drive wealthier museums to outsource software development by licensing commercial products, and relegate collections unable to afford software licenses, to bespoke, simple, or no software solutions? This session will include project case studies on the economics of collections research cyberinfrastructure and present perspectives and paths to long-term sustainability.

The research and practice of spacecraft software engineering

In order to ensure the safety and reliability of spacecraft software products, it is necessary to execute engineering management. Firstly, the paper introduces the problems of unsystematic planning, uncertain classified management and uncontinuous improved mechanism in domestic and foreign spacecraft software engineering management. Then, it proposes a solution for software engineering management based on system-integrated ideology in the perspective of spacecraft system. Finally, a application result of spacecraft is given as an example. The research can provides a reference for executing spacecraft software engineering management and improving software product quality.

The Path Extended from Organizational Culture to Innovative Work Behavior: A Research on a Defense Company

The Defense Industry field has characteristics that make for a unique working environment. This paper presents a study conducted among the Software Engineering (SWE) employees working at a software development company in defense industry, which examined the relationship between the constructs; organizational culture, job satisfaction, innovative work behavior and the employees’ valuation of the external recognition. One hundred and forty one employees filled out the questionnaire. It was determined that there were positive relations between organizational culture and job satisfaction, whereas positive correlations were determined between job satisfaction and innovative work behavior as well as external recognition. The Structural Equation Modeling (SEM) employed to study the relationship grids among the observed variables. Limitations of the study are also presented along with future research recommendations. SWE managers can use this information to increase employee job satisfaction and innovative work behavior.

Topological Decomposition of Directed Graphs

The analysis of directed graphs is important in application areas like software engineering, bioinformatics, or project management. Distinguishing between topological structures such as cyclic and hierarchical subgraphs provides the analyst with important information. However, until now, graph drawing algorithms draw the complete directed graph either hierarchically or cyclic. Therefore, we introduced new algorithms for decomposing the input graph into cyclic subgraphs, directed acyclic subgraphs, and tree subgraphs. For all of these subgraphs, optimized layout algorithms exist. We developed and presented a new algorithm for drawing the complete graph based on the decomposition using and combining these layouts. In this paper, we focus on the algorithms for the topological decomposition. We describe them on an intermediate level complementing the previous descriptions on the high and the low level. Besides the motivation, illustrative examples of all cases that need to be considered by the algorithm, standard as well as more complex ones, are given. We complement this description by a complexity analysis of all algorithms.